Управління мережами мобільного зв’язку 5G за допомогою використання технологій штучного інтелекту

The article is devoted to the problem of excessive traffic of base station cells. In order to reduce the
impact of this problem on the quality of services of mobile network operators, it is proposed to use
artificial intelligence (AI) technology to analyze and predict the load on the network. AI is great for
wireless environments, as it has a lot of data available for analysis and obtaining certain patterns.
The article proposes a model of machine learning and neural network architecture for forecasting
the load on 5G cells.

Method of Dynamic RAN Synthesis for 5G Networks

Nowadays, plenty of smart phones and tablets result in increased demands for bandwidth and availability of mobile networks. According to recent studied, 5G is expected to bring significant improvement such as 10-100-fold peak data rates, 1000-fold network capacity and 10-fold energy efficiency. There are two key enablers of these requirements: ultra-dense deployment of small cells and centralized signal processing.

Radio Access Network Model With Adaptive Structure Synthesis

Constantly increasing demand by mobile devices for higher data rates and new multimedia services support creates unprecedented challenges for future fifth generation (5G) mobile networks: 1000 times higher system capacity, up to 100 times higher peak user data rates and 10 times lower energy efficiency of today’s 4G networks.